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Jonathan Krause

ResearcherPublications, citations & collaboration network

Jonathan Krause is a researcher indexed in ScholarIQ from OpenAlex & ORCID. ScholarIQ records 93 works, 49,784 citations, an h-index of 30 and an i10-index of 42.

93
Works
49,784
Citations
30
h-index
42
i10-index

How has Jonathan Krause's publication output changed over time?

ScholarIQpublication output · 2013–2019

Output grew0% over the shown period — from 1 works in 2013 to 1 in 2019.

1
2
1
2
3
1
201320152016201720182019

What are the most-cited papers on Jonathan Krause?

ScholarIQmost cited works
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael S. Bernstein, Alexander C. Berg, Li Fei-Fei
S25538012. 201540,426 Citations
3D Object Representations for Fine-Grained Categorization
Jonathan Krause, Michael Stark, Jia Deng, Li Fei-Fei
20133,486 Citations
Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy
Jonathan Krause, Varun Gulshan, Ehsan Rahimy, Peter A. Karth, Kasumi Widner, Greg S. Corrado, Lily Peng, Dale R. Webster
Ophthalmology. 2018562 CitationsOPEN ACCESS
How to Read Articles That Use Machine Learning
Yun Liu, Po-Hsuan Cameron Chen, Jonathan Krause, Lily Peng
JAMA. 2019522 Citations
Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States
Timnit Gebru, Jonathan Krause, Yilun Wang, Duyun Chen, Jia Deng, Erez Lieberman Aiden, Li Fei-Fei
Proceedings of the National Academy of Sciences. 2017499 CitationsOPEN ACCESS

Related on ScholarIQ

Saint John Vianney College Seminary
Institution
ImageNet Large Scale Visual Recognition Challenge
Paper
3D Object Representations for Fine-Grained Categorization
Paper
Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy
Paper
How to Read Articles That Use Machine Learning
Paper
Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States
Paper
470M+ articles · free account